CUDACasts Episode #8: Accelerate FFTW Apps with CUFFT 5.5

GPU libraries provide an easy way to accelerate applications without writing any GPU-specific code. With the new CUDA 5.5 version of the NVIDIA CUFFT Fast Fourier Transform library, FFT acceleration gets even easier, with new support for the popular FFTW API. It is now extremely simple for developers to accelerate existing FFTW library calls on the GPU, sometimes with no code changes! By simply changing the linker command line to link the CUFFT library instead of the FFTW library, you can take advantage of the GPU with only a re-link. In today’s CUDACast, we take a simple application that uses the standard FFTW library, and accelerate the function calls on the GPU by simply changing which library we link. In fact, the only code change we will make is to use the cufftw.h header file. This ensures that, at compile time, we are not calling any unsupported functions.

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About Mark Ebersole

As CUDA Educator at NVIDIA, Mark Ebersole teaches developers and programmers about the NVIDIA CUDA parallel computing platform and programming model, and the benefits of GPU computing. With more than ten years of experience as a low-level systems programmer, Mark has spent much of his time at NVIDIA as a GPU systems diagnostics programmer in which he developed a tool to test, debug, validate, and verify GPUs from pre-emulation through bringup and into production. Before joining NVIDIA, he worked for IBM developing Linux drivers for the IBM iSeries server. Mark holds a BS degree in math and computer science from St. Cloud State University. Follow @cudahamster on Twitter